快速匹配追踪三参数时频特征滤波
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摘要
传统的匹配追踪方法通常采用完备的时频原子库和贪婪算法进行子波分解,计算量巨大。为此本文引入互相关阈值约束技术,实现两次迭代和完备库之间的反馈,剔除那些互相关值很小的时频原子,动态地减小完备库的冗余度;通过多原子同步提取,实现快速匹配追踪地震道分解。分解后的地震信号是按子波的能量排序的,每个子波都由振幅、频率和中心时间三参数表示,代表原始地震信号在某一中心时间的局部主振幅特征和主频率特征,因此在信号重构时,可根据有效信号与噪声信号的主振幅、主频率和中心时间的差异,构建三参数时频特征滤波器,筛选出代表有效信号的子波对信号进行重构,达到无损去噪的目的。合成地震记录和实际资料处理结果表明了该方法的有效性。
Matching pursuit (MP) algorithm can adaptively decomposes a seismic trace into a series of constituent wavelets. Conventional matching pursuit decompositions usually need a sufficiently large atom dictionary and greedy algorithms to decompose wavelet with timeconsumed calculations. Therefor,we introduce a thresholdconstrained crosscorrelation approach. This approach implement a feedback loop between the iterations and the dictionary,and atoms with correlation ratios below the threshold are rejected. It can selfadaptive reduce the size of dictionary. Fast matching pursuit seismic trace decomposition is achieved through multiple atom extractions. After decomposition,each wavelet sorted in energy was expressed by three parameters,amplitude,frequency and centre time,which represents major amplitude and dominant frequency of original signals at a centre time. According to the difference of the major amplitude,dominant frequency and centre time between signal and noise,we construct a three parameter filter,and extract the signal wavelets to reconstruct the seismic trace to filter noise without signal damage. Tests on synthetic and real data show the effectiveness of the proposed method.
Matching pursuit (MP) algorithm can adaptively decomposes a seismic trace into a series of constituent wavelets. Conventional matching pursuit decompositions usually need a sufficiently large atom dictionary and greedy algorithms to decompose wavelet with timeconsumed calculations. Therefor,we introduce a thresholdconstrained crosscorrelation approach. This approach implement a feedback loop between the iterations and the dictionary,and atoms with correlation ratios below the threshold are rejected. It can selfadaptive reduce the size of dictionary. Fast matching pursuit seismic trace decomposition is achieved through multiple atom extractions. After decomposition,each wavelet sorted in energy was expressed by three parameters,amplitude,frequency and centre time,which represents major amplitude and dominant frequency of original signals at a centre time. According to the difference of the major amplitude,dominant frequency and centre time between signal and noise,we construct a three parameter filter,and extract the signal wavelets to reconstruct the seismic trace to filter noise without signal damage. Tests on synthetic and real data show the effectiveness of the proposed method.
引文
[1]Mallat S,Zhang Z.Matching pursuits with time-frequency dictionaries.IEEE Transactions on SignalProcessing,1993,41(12):3397～3415
[2]Liu J L,Han W,Li X.Time-Frequency decomposi-tionbased on Ricker wavelet.SEG Technical ProgramExpanded Abstracts,2004,23:1937～1940
[3]Liu J L,Marfurt J K.Matching pursuit decompositionusing Morlet wavelet.SEG Technical Program Ex-panded Abstracts,2005,24:786～789
[4]Wang Y H.Seismic time-frequency spectral decomposi-tion by matching pursuit.Geophysics,2007,72(1):V13～V20
[5]Wang Yanghua.Multichannel matching pursuit forseismic trace decomposition.Geophysics,2010,75(4):V61～V66
[6]张繁昌,李传辉,印兴耀.基于动态匹配子波库的地震数据快速匹配追踪.石油地球物理勘探,2010,45(5):667～673Zhang Fanchang,Li Chuanhui and Yin Xingyao.Seis-mic data fast matching pursuit based on dynamic matc-hing wavelet library.OGP,2010,45(5):667～673
[7]宋新武,郑浚茂,范兴燕等.基于Ricker子波匹配追踪算法在薄互层砂体储层预测中的应用.吉林大学学报(地球科学版),2011,41(1):387～392Song Xinwu,Zheng Junmao,Fan Xingyan et al.Appli-cation of the thin-interbedded reservoir predictionbased on Ricker wavelet match tracing algorithm.Journal of Jilin University(Earth Science Edition),2011,41(1):387～392
[8]Yang Hao,Zheng Xiaodong,Ma Shufang.Thin-bedreflectivity inversion based on matching pursuit.SEGTechnical Program Expanded Abstracts,2011,30:2586～2590
[9]邹少锋.基于雷克子波的匹配追踪子波分解方法研究[硕士学位论文].北京:中国石油大学(北京)地球物理与信息工程学院物探系,2011
[2]Liu J L,Han W,Li X.Time-Frequency decomposi-tionbased on Ricker wavelet.SEG Technical ProgramExpanded Abstracts,2004,23:1937～1940
[3]Liu J L,Marfurt J K.Matching pursuit decompositionusing Morlet wavelet.SEG Technical Program Ex-panded Abstracts,2005,24:786～789
[4]Wang Y H.Seismic time-frequency spectral decomposi-tion by matching pursuit.Geophysics,2007,72(1):V13～V20
[5]Wang Yanghua.Multichannel matching pursuit forseismic trace decomposition.Geophysics,2010,75(4):V61～V66
[6]张繁昌,李传辉,印兴耀.基于动态匹配子波库的地震数据快速匹配追踪.石油地球物理勘探,2010,45(5):667～673Zhang Fanchang,Li Chuanhui and Yin Xingyao.Seis-mic data fast matching pursuit based on dynamic matc-hing wavelet library.OGP,2010,45(5):667～673
[7]宋新武,郑浚茂,范兴燕等.基于Ricker子波匹配追踪算法在薄互层砂体储层预测中的应用.吉林大学学报(地球科学版),2011,41(1):387～392Song Xinwu,Zheng Junmao,Fan Xingyan et al.Appli-cation of the thin-interbedded reservoir predictionbased on Ricker wavelet match tracing algorithm.Journal of Jilin University(Earth Science Edition),2011,41(1):387～392
[8]Yang Hao,Zheng Xiaodong,Ma Shufang.Thin-bedreflectivity inversion based on matching pursuit.SEGTechnical Program Expanded Abstracts,2011,30:2586～2590
[9]邹少锋.基于雷克子波的匹配追踪子波分解方法研究[硕士学位论文].北京:中国石油大学(北京)地球物理与信息工程学院物探系,2011
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